Chuen-Lung Chen

An application of genetic algorithms for flow shop problems

Abstract This research studies an application of genetic algorithms for flow shop problems with makespan as the criterion. We generate a genetic Algorithm (GA) based heuristic for these problems, and compare the computational results of the heuristic with the results of some existing heuristics. The conclusions show that the GA based heuristic can always give the best results in a short time on a SUN workstation.

Genetic algorithms applied to the continuous flow shop problem

This research develops an approach for applying Genetic Algorithms (GA) to scheduling problems. We generate a GA based heuristic for continuous flow shop problems with total flow time as the criterion. The effects of several crucial factors of GA on the performance of the heuristic for the problem are explored in detail. The computational experience of heuristic provides several observations of the application of GA, and strongly supports that the applications of GA are problem specific. The computational experience also shows that GA can be good techniques for scheduling problems.

Complexity of single machine, multi-criteria scheduling problems

Abstract We examine the complexity of scheduling problems when more than one measure of performance is appropriate. The criteria we study are maximal tardiness, flowtime, number of tardy jobs, tardiness and the weighted counterparts of the last three measures. The machine environment is restricted to a single machine. Complexity results are given for secondary criterion, bicriteria and weighted criteria approaches for all combinations of measures. Of the problems examined, only six remain open.

Genetic algorithms for the two-stage bicriteria flowshop problem

Abstract This paper considers the two-stage bicriteria flow shop scheduling problem with the objective of minimizing the total flow time subject to obtaining the optimal makespan. In view of the NP-hard nature of the problem, two Genetic Algorithms (GA) based approaches are proposed to solve the problem. The effectiveness of the proposed GA based approaches is demonstrated by comparing their performance with the only known heuristic for the problem. The computational experiments show that the proposed GA based approaches are effective in solving the problem and recommend that the proposed GA based approaches are useful for solving the multi-machine, multi-criteria scheduling problems.

A tabu search approach to the cell formation problem

Abstract The formation of machine cells and part families is a central issue in the design of cellular production systems In this paper, we propose a tabu search based approach to deal with this problem by modeling it as a “Shortest Spanning Path” problem with respect to both parts and machines. A comparison of the proposed method with some of the existing methods is presented. Our results revealed that the proposed approach possesses several advantages that make it capable of handling the problem addressed in this paper as it exists in real-world situations.

Development of a strategic research plan for an academic department through the use of quality function deployment

Abstract Quality Function Deployment (QFD) is a popular approach for formalizing the process of listening to “the voice of the customer,” and assigning responsibilities to members of an organization in an effort to respond effectively to customer needs, QFD is being used by the Department of Industrial Engineering at Mississippi State University to help identify key customers for departmental research efforts, to identify and track the research needs of those customers, to fashion a comprehensive strategic plan for departmental research activities based on customer needs, to deploy various research functions and responsibilities to specific faculty members or groups, and to track research performance relative to goals. This approach appears to be an excellent means of formalizing the process of strategic research planning.

Scheduling unit processing time jobs on a single machine with multiple criteria

Abstract We examine single machine scheduling problems when all jobs have identical processing times and there are two measures of performance. The measures of performance considered are flow-time, tardiness, number of tardy jobs, the weighted counterparts for these three measures and maximum tardiness. Using the assignment model as a basis, we provide efficient algorithms for the problem when a utility function is given, when one criterion is considered to be primary and the other one secondary. We also develop algorithms that arc polynomial in the number of nondominatcd schedules to generate all nondominated schedules. Finally, we show that the methods can easily be extended to handle more than two criteria, as well as nonzero release dales.

Designing a tabu search algorithm for the two-stage flow shop problem with secondary criterion

This paper discusses the process of desigining a tabu search-based heuristic for the two-stage flow shop problem with makespan minimization as the primary criterion and the minimization of total flow time as the secondary criterion. A factorial experiment is designed to analyse thoroughly the effects of four different factors, i.e. the initial solution, type of move, size of neighbourhood and the list size, on the performance of the tabu search-based heuristic. Using the techniques of evolution curves, and response tables and response graphs, coupled with the Taguchi method, the best combination of the factors for the tabu search-based heuristic is identified, and the effectiveness of the heuristic algorithm in finding an optimal solution is evaluated by comparing its performance with the best known heuristic to solve this problem.

A bottleneck-based heuristic for minimizing makespan in a flexible flow line with unrelated parallel machines

This study developed a bottleneck-based heuristic (BBFFL) to solve a flexible flow line problem with a bottleneck stage, where unrelated parallel machines exist in all the stages, with the objective of minimizing the makespan. The essential idea of BBFFL is that scheduling jobs at the bottleneck stage may affect the performance of a heuristic for scheduling jobs in all the stages. Therefore, in BBFFL, a variant of Johnsons rule is used to develop a bottleneck-based initial sequence generator (BBISG). Then, a bottleneck-based multiple insertion procedure (BBMIP) is applied to the initial sequence to control the order by which jobs enter the bottleneck stage to be the same as that at the first stage. Five experimental factors were used to design 243 different production scenarios and 10 test problems were randomly generated in each scenario. These test problems were used to compare the performance of BBFFL with several well-known heuristics. Computational results show that the BBFFL significantly outperforms all the well-known heuristics.

Bottleneck-based heuristics to minimize total tardiness for the flexible flow line with unrelated parallel machines

This paper considers the flexible flow line problem with unrelated parallel machines at each stage and with a bottleneck stage on the line. The objective of the problem is to minimize the total tardiness. Two bottleneck-based heuristics with three machine selection rules are proposed to solve the problem. The heuristics first develop an indicator to identify a bottleneck stage in the flow line, and then separate the flow line into the upstream stages, the bottleneck stage, and the downstream stages. The upstream stages are the stages ahead of the bottleneck stage and the downstream stages are the stages behind the bottleneck stage. A new approach is developed to find the arrival times of the jobs at the bottleneck stage. Using the new approach, the bottleneck-based heuristics develop two decision rules to iteratively schedule the jobs at the bottleneck stage, the upstream stages, and the downstream stages. In order to evaluate the performance of the bottleneck-based heuristics, seven commonly used dispatching rules and a basic tabu search algorithm are investigated for comparison purposes. Seven experimental factors are used to design 128 production scenarios, and ten test problems are generated for each scenario. Computational results show that the bottleneck-based heuristics significantly outperform all the dispatching rules for the test problems. Although the effective performance of the bottleneck-based heuristics is inferior to the basic tabu search algorithm, the bottleneck-based heuristics are much more efficient than the tabu search algorithm. Also, a test of the effect of the experimental factors on the dispatching rules, the bottleneck-based heuristics, and the basic tabu search algorithm is performed, and some interesting insights are discovered.